DBMS > Brytlyt vs. Manticore Search vs. MySQL vs. SAP IQ vs. Stardog

System Properties Comparison Brytlyt vs. Manticore Search vs. MySQL vs. SAP IQ vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

Columnar RDBMS optimized for Big Data analytics

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

column-oriented

Graph DBMS
RDF store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

brytlyt.io

manticoresearch.com

www.mysql.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.stardog.com

Technical documentation

docs.brytlyt.io

manual.manticoresearch.com

dev.mysql.com/doc

help.sap.com/docs/SAP_IQ

docs.stardog.com

Developer

Brytlyt

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

SAP, formerly Sybase

Stardog-Union

Initial release

2016

2017

1995

1994

2010

Current release

5.0, August 2023

6.0, February 2023

9.0.0, July 2024

16.1 SPS04, April 2019

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and CUDA

C++

C and C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

Fixed schema

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML-type available, but no XML query functionality.

Can index from XML

yes

Import/export of XML data possible

Secondary indexes

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

yes

proprietary syntax

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

SAP/Sybase Replication Server

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

Access rights for users and roles

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